CN113037162B - Bearingless Permanent Magnet Synchronous Motor Neural Network Bandpass Filter Vibration Compensation Controller - Google Patents

Bearingless Permanent Magnet Synchronous Motor Neural Network Bandpass Filter Vibration Compensation Controller Download PDF

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CN113037162B
CN113037162B CN202110195977.3A CN202110195977A CN113037162B CN 113037162 B CN113037162 B CN 113037162B CN 202110195977 A CN202110195977 A CN 202110195977A CN 113037162 B CN113037162 B CN 113037162B
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CN113037162A (en
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朱熀秋
王鑫
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Jiangsu University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/05—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation specially adapted for damping motor oscillations, e.g. for reducing hunting
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/0014—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using neural networks
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16C—SHAFTS; FLEXIBLE SHAFTS; ELEMENTS OR CRANKSHAFT MECHANISMS; ROTARY BODIES OTHER THAN GEARING ELEMENTS; BEARINGS
    • F16C32/00—Bearings not otherwise provided for
    • F16C32/04—Bearings not otherwise provided for using magnetic or electric supporting means
    • F16C32/0406—Magnetic bearings
    • F16C32/044—Active magnetic bearings
    • F16C32/0474—Active magnetic bearings for rotary movement
    • F16C32/0493—Active magnetic bearings for rotary movement integrated in an electrodynamic machine, e.g. self-bearing motor
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02N—ELECTRIC MACHINES NOT OTHERWISE PROVIDED FOR
    • H02N15/00—Holding or levitation devices using magnetic attraction or repulsion, not otherwise provided for
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/18—Estimation of position or speed
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/22—Current control, e.g. using a current control loop
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using DC to AC converters or inverters
    • H02P27/08—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using DC to AC converters or inverters with pulse width modulation
    • H02P27/085—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using DC to AC converters or inverters with pulse width modulation wherein the PWM mode is adapted on the running conditions of the motor, e.g. the switching frequency

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  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Ac Motors In General (AREA)
  • Control Of Electric Motors In General (AREA)
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Abstract

本发明公开一种无轴承永磁同步电机神经网络带通滤波器振动补偿控制器，由位移控制器和转速控制器组成，位移控制器包括振动力补偿控制模块和死区振动补偿模块；振动力补偿控制模块以实际位移与转子机械角度作为输入，输出对应的振动补偿力，由第一神经网络带通滤波器、第二神经网络带通滤波器和第三PID控制器、第四PID控制器组成；死区振动补偿模块以转子电角度与交直轴电流实际电流作为输入，输出交直轴补偿电压，由直轴方向的第三神经网络带通滤波器、交轴方向的第四神经网络带通滤波器以及第六PI控制器、第七PI控制器组成；本发明不仅对偏心问题造成的振动进行分析补偿，还对死区效应造成的振动进行补偿控制，使悬浮控制精度得到有效提高。

Figure 202110195977

The invention discloses a vibration compensation controller of a bearingless permanent magnet synchronous motor neural network band-pass filter, which is composed of a displacement controller and a rotational speed controller. The displacement controller includes a vibration force compensation control module and a dead zone vibration compensation module; the vibration force The compensation control module takes the actual displacement and the mechanical angle of the rotor as input, and outputs the corresponding vibration compensation force. The dead-zone vibration compensation module takes the rotor electrical angle and the actual current of the AC-direction axis as input, and outputs the AC-direction axis compensation voltage. The filter is composed of the sixth PI controller and the seventh PI controller; the invention not only analyzes and compensates the vibration caused by the eccentricity problem, but also compensates and controls the vibration caused by the dead zone effect, so that the suspension control accuracy is effectively improved.

Figure 202110195977

Description

无轴承永磁同步电机神经网络带通滤波器振动补偿控制器Bearingless Permanent Magnet Synchronous Motor Neural Network Bandpass Filter Vibration Compensation Controller

技术领域technical field

本发明属于无轴承电机控制领域，涉及无轴承永磁同步电机死区补偿控制与转子偏心控制技术，用于对无轴承永磁同步电机的振动进行补偿控制。The invention belongs to the field of bearingless motor control, relates to dead zone compensation control and rotor eccentricity control technology of a bearingless permanent magnet synchronous motor, and is used for compensating and controlling the vibration of the bearingless permanent magnet synchronous motor.

背景技术Background technique

无轴承永磁同步电机是一种高转速，高精度及无需润滑的新型特种电机，在航天航空、化工制造、半导体工业及其他需要特殊环境的领域中具有越来越广泛的应用前景。无轴承永磁同步电机作为旋转驱动电机，由于材质不均、加工误差以及装配误差等问题，不可避免会存在一定程度的转子质量偏心，在旋转时产生于转速同频的离心激振力。同时，在无轴承永磁同步电机控制过程中，必须设置死区时间来避免逆变器上下桥臂短路，而死区时间的引入使电流谐波增加，进一步增大了不平衡力的幅值，导致转子不平衡振动，影响转子的悬浮控制精度。Bearingless permanent magnet synchronous motor is a new type of special motor with high speed, high precision and no lubrication. It has more and more extensive application prospects in aerospace, chemical manufacturing, semiconductor industry and other fields that require special environments. Bearingless permanent magnet synchronous motor as a rotating drive motor, due to uneven material, processing error and assembly error, there will inevitably be a certain degree of rotor mass eccentricity, which will generate centrifugal excitation force at the same frequency of rotation during rotation. At the same time, in the control process of the bearingless permanent magnet synchronous motor, the dead time must be set to avoid the short circuit of the upper and lower bridge arms of the inverter, and the introduction of the dead time increases the current harmonics and further increases the amplitude of the unbalanced force , resulting in unbalanced vibration of the rotor, affecting the suspension control accuracy of the rotor.

关于无轴承永磁同步电机的转子不平衡振动控制，现有技术大多是对转子质量偏心造成的不平衡振动进行补偿控制，而对由死区效应引起的不平衡振动却鲜有提及。中国专利公开号为CN104659990A的文献公开了无轴承电机的自适应滤波不平衡振动位移提取方法，为无轴承电机振动补偿控制的首要条件做出铺垫。中国专利公开号为CN105048913A的文献公开了一种基于电流补偿的无轴承异步电机不平衡振动控制系统，通过调节补偿电流实现悬浮振动补偿控制。但是，这些方案中对无轴承电机的振动补偿控制主要以偏心造成的振动情况进行检测与补偿，而对死区效应造成的振动却尚未提及。为提高无轴承永磁同步电机不平衡振动位移控制的精度，不仅需要对由转子质量偏心造成的转子偏心位移进行补偿，还需对死区效应造成的转子不平衡振动进行补偿，这是实现高精度无轴承永磁同步电机控制的重中之重。Regarding the rotor unbalanced vibration control of the bearingless permanent magnet synchronous motor, the prior art mostly compensates and controls the unbalanced vibration caused by the eccentricity of the rotor mass, but seldom mentions the unbalanced vibration caused by the dead zone effect. The Chinese Patent Publication No. CN104659990A discloses an adaptive filtering unbalanced vibration displacement extraction method of a bearingless motor, which lays the groundwork for the primary condition of vibration compensation control of a bearingless motor. The Chinese Patent Publication No. CN105048913A discloses an unbalanced vibration control system for a bearingless asynchronous motor based on current compensation, which realizes suspension vibration compensation control by adjusting the compensation current. However, in these schemes, the vibration compensation control of the bearingless motor mainly detects and compensates for the vibration caused by the eccentricity, while the vibration caused by the dead zone effect has not been mentioned yet. In order to improve the accuracy of the unbalanced vibration displacement control of the bearingless permanent magnet synchronous motor, it is not only necessary to compensate for the rotor eccentric displacement caused by the rotor mass eccentricity, but also to compensate for the rotor unbalanced vibration caused by the dead zone effect. Precision bearingless permanent magnet synchronous motor control is a top priority.

发明内容SUMMARY OF THE INVENTION

本发明的目的是提供一种无轴承永磁同步电机神经网络带通滤波器振动补偿控制器,能抑制无轴承永磁同步电机振动的振动补偿，以解决现有无轴承永磁同步电机在振动补偿控制中只对转子质量偏心进行振动补偿，而忽视死区效应引起的振动问题，从而实现电机转子的稳定悬浮及高效运行，并提高电机控制精度，更好地应用于电气传动系统。The purpose of the present invention is to provide a vibration compensation controller of a bearingless permanent magnet synchronous motor neural network band-pass filter, which can suppress the vibration compensation of the bearingless permanent magnet synchronous motor, so as to solve the problem of the vibration of the existing bearingless permanent magnet synchronous motor. In the compensation control, only the vibration compensation is performed on the eccentricity of the rotor mass, and the vibration problem caused by the dead zone effect is ignored, so as to realize the stable suspension and efficient operation of the motor rotor, and improve the motor control accuracy, which is better applied to the electrical transmission system.

本发明提供的无轴承永磁同步电机神经网络带通滤波器振动补偿控制器所采用的技术方案是：其由位移控制器和转速控制器组成，所述的位移控制器包括振动力补偿控制模块和死区振动补偿模块；The technical solution adopted by the vibration compensation controller of the neural network band-pass filter of the bearingless permanent magnet synchronous motor provided by the present invention is: it is composed of a displacement controller and a rotational speed controller, and the displacement controller includes a vibration force compensation control module and dead zone vibration compensation module;

所述的振动力补偿控制模块以x，y方向上的实际位移x，y与转子机械角度θm作为输入，输出对应的振动补偿力Fxh，Fyh，由第一神经网络带通滤波器、第二神经网络带通滤波器和第三PID控制器、第四PID控制器组成；所述的第一神经网络带通滤波器以x方向上的实际位移x与转子机械角度θm作为输入，输出振动位移

Figure BDA0002946540100000021
以0作为给定值与振动位移
Figure BDA0002946540100000022
作差并将该差值作为第三PID控制器的输入，第三PID控制器输出振动补偿力Fxh；第二神经网络带通滤波器以y方向上的实际位移y与转子机械角度θm作为输入，输出振动位移
Figure BDA0002946540100000023
以0作为给定值与振动位移
Figure BDA00029465401000000212
作差并将该差值作为第四PID控制器的输入，第四PID控制器输出振动补偿力Fyh；所述的振动补偿力Fxh与悬浮绕组x方向的力的给定值Fx求和后输入给力电流转换模块；所述的振动补偿力Fyh与悬浮绕组y方向的力的给定值Fy求和后输入给力电流转换模块，电流转换模块获得交直轴电流给定值
Figure BDA0002946540100000024
和
Figure BDA0002946540100000025
The vibration force compensation control module takes the actual displacement x, y in the x, y direction and the rotor mechanical angle θ m as input, and outputs the corresponding vibration compensation force F xh , F yh , which is determined by the first neural network band-pass filter. , the second neural network band-pass filter, the third PID controller and the fourth PID controller are composed; the first neural network band-pass filter takes the actual displacement x in the x direction and the rotor mechanical angle θ m as the input , the output vibration displacement
Figure BDA0002946540100000021
Take 0 as the given value and the vibration displacement
Figure BDA0002946540100000022
Make a difference and use the difference as the input of the third PID controller, the third PID controller outputs the vibration compensation force F xh ; the second neural network band-pass filter uses the actual displacement y in the y direction and the rotor mechanical angle θ m As input, output vibration displacement
Figure BDA0002946540100000023
Take 0 as the given value and the vibration displacement
Figure BDA00029465401000000212
Make a difference and use this difference as the input of the 4th PID controller, the 4th PID controller outputs the vibration compensation force F yh ; the given value F x of the described vibration compensation force F xh and the force of the suspension winding x direction is calculated After the sum, input the force-current conversion module; the given value F y of the described vibration compensation force F yh and the force in the y-direction of the suspension winding is summed and input to the force-current conversion module, and the current conversion module obtains the AC-direction axis current given value
Figure BDA0002946540100000024
and
Figure BDA0002946540100000025

所述的死区振动补偿模块以转子电角度θe与交直轴电流实际电流iBq，iBd作为输入，输出交直轴补偿电压uBqh，uBdh，由直轴方向的第三神经网络带通滤波器、交轴方向的第四神经网络带通滤波器以及第六PI控制器、第七PI控制器组成，第三神经网络带通滤波器以直轴方向上的实际电流iBd与转子电角度θe的6倍作为输入，得到直轴方向的谐波电流

Figure BDA0002946540100000026
以0作为给定值与谐波电流
Figure BDA0002946540100000027
作差并将结果作为第六PI控制器的输入，第六PI控制器得到直轴补偿电压uBdh，将直轴方向上的控制电压uBd与直轴补偿电压uBdh相加获得直轴指令电压
Figure BDA0002946540100000028
第四神经网络带通滤波器以交轴方向上的实际电流iBq与转子电角度θe的6倍作为输入，得到直轴方向的谐波电流
Figure BDA0002946540100000029
以0作为给定值与谐波电流
Figure BDA00029465401000000210
作差并将结果作为第七PI控制器的输入，第七PI控制器得到交轴补偿电压uBqh，将交轴方向上的控制电压uBq与交轴补偿电压uBqh相加获得交轴指令电压
Figure BDA00029465401000000211
The dead zone vibration compensation module takes the rotor electrical angle θ e and the actual currents i Bq , i Bd as input, and outputs the compensation voltages u Bqh and u Bdh in the direct axis, which are band-passed by the third neural network in the direction of the direct axis. The filter, the fourth neural network bandpass filter in the quadrature axis direction, the sixth PI controller and the seventh PI controller are composed. The third neural network bandpass filter uses the actual current i Bd in the direct axis direction and the rotor current 6 times the angle θ e is used as input to obtain the harmonic current in the direction of the direct axis
Figure BDA0002946540100000026
Taking 0 as a given value and harmonic current
Figure BDA0002946540100000027
Make a difference and use the result as the input of the sixth PI controller, the sixth PI controller obtains the direct axis compensation voltage u Bdh , and adds the control voltage u Bd in the direct axis direction and the direct axis compensation voltage u Bdh to obtain the direct axis command Voltage
Figure BDA0002946540100000028
The fourth neural network band-pass filter takes the actual current i Bq in the quadrature axis direction and 6 times the rotor electrical angle θ e as input, and obtains the harmonic current in the direct axis direction
Figure BDA0002946540100000029
Taking 0 as a given value and harmonic current
Figure BDA00029465401000000210
Make a difference and use the result as the input of the seventh PI controller, the seventh PI controller obtains the quadrature axis compensation voltage u Bqh , and adds the control voltage u Bq in the quadrature axis direction and the quadrature axis compensation voltage u Bqh to obtain the quadrature axis command Voltage
Figure BDA00029465401000000211

本发明的有益效果是：The beneficial effects of the present invention are:

1)本发明采用死区振动补偿控制，不仅对死区进行了补偿，还能有效地抑制无轴承永磁同步电机运行过程中的振动，提高悬浮控制精度。1) The present invention adopts the dead zone vibration compensation control, which not only compensates the dead zone, but also effectively suppresses the vibration during the operation of the bearingless permanent magnet synchronous motor, and improves the suspension control accuracy.

2)本发明采用的神经网络带通滤波器，工作原理简单，计算过程简洁，并可以根据电机的实时转速获取所需的信号。2) The neural network band-pass filter adopted in the present invention has simple working principle and simple calculation process, and can obtain the required signal according to the real-time speed of the motor.

3)本发明采用PI控制器对振动进行调节，该控制器原理简单，系数调整便捷，并且具有较强的鲁棒性。3) The present invention adopts the PI controller to adjust the vibration. The controller has simple principle, convenient coefficient adjustment and strong robustness.

4)在无轴承永磁同步电机振动补偿控制中，一般只考虑由偏心因素造成的振动并实施补偿控制，而死区效应引起的振动问题却未曾有人提及，这样对整个悬浮控制的精度是不利的。本发明为了使无轴承永磁同步电机有更高的悬浮控制精度，不仅对偏心问题造成的振动进行分析补偿，还对死区效应造成的振动进行补偿控制，使悬浮控制精度得到有效提高。4) In the vibration compensation control of the bearingless permanent magnet synchronous motor, generally only the vibration caused by the eccentric factor is considered and the compensation control is implemented, while the vibration problem caused by the dead zone effect has not been mentioned, so the accuracy of the entire suspension control is Adverse. In order to make the bearingless permanent magnet synchronous motor have higher suspension control accuracy, the invention not only analyzes and compensates the vibration caused by the eccentricity problem, but also compensates and controls the vibration caused by the dead zone effect, so that the suspension control accuracy is effectively improved.

附图说明Description of drawings

为使本发明的内容更加明显易懂，以下结合附图和具体实施方式对本发明进行详细描述：In order to make the content of the present invention more obvious and easy to understand, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments:

图1是本发明所述的结构原理框图；Fig. 1 is the structural principle block diagram of the present invention;

图2是图1中转速控制器2的结构原理框图；Fig. 2 is the structural principle block diagram of the rotational speed controller 2 in Fig. 1;

图3是图1中位移控制器1的结构原理框图；Fig. 3 is the structural principle block diagram of the displacement controller 1 in Fig. 1;

图4是图3中x方向与y方向的振动力补偿模块5原理框图；Fig. 4 is the principle block diagram of the vibration force compensation module 5 in the x direction and the y direction in Fig. 3;

图5是图3中直轴方向与交轴方向的死区振动补偿模块6原理框图；FIG. 5 is a schematic block diagram of the dead zone vibration compensation module 6 in the direction of the straight axis and the direction of the quadrature axis in FIG. 3;

图6是图4中第一神经网络带通滤波器51的内部结构原理框图；Fig. 6 is the internal structure principle block diagram of the first neural network bandpass filter 51 in Fig. 4;

图7是图5中第二神经网络带通滤波器53的内部结构原理框图；Fig. 7 is the internal structure principle block diagram of the second neural network bandpass filter 53 in Fig. 5;

图8是图6中第三神经网络带通滤波器61的内部结构原理框图；Fig. 8 is the internal structure principle block diagram of the third neural network bandpass filter 61 in Fig. 6;

图9是图7中第四神经网络带通滤波器63的内部结构原理框图；Fig. 9 is the internal structure principle block diagram of the fourth neural network bandpass filter 63 in Fig. 7;

图10是本发明所述的电机振动补偿控制器结构总体实现原理框图。FIG. 10 is a schematic block diagram of the overall realization of the structure of the motor vibration compensation controller according to the present invention.

图中：1.位移控制器；2.转速控制器；3.无轴承永磁同步电机；11.第一PID控制器；12.第二PID控制器；13.力电流转换模块；14.第四PI控制器；15.第五PI控制器；16.第三坐标变换模块；17.角度计算模块；21.第一PI控制器；22.第二PI控制器；23.第三PI控制器；24.第一坐标变换模块；25.第二坐标变换模块；26.第一SVPWM逆变器；27.编码器；28.速度计算模块；5.振动力补偿模块；51.第一神经网络带通滤波器；52.第三PID控制器；53.第二神经网络带通滤波器；54.第四PID控制器；55.第一权值调整模块；56.第二权值调整模块；6.死区振动补偿模块；61.第三神经网络带通滤波器；62.第六PI控制器；63.第四神经网络带通滤波器；64.第七PI控制器；65.第三权值调整模块；66.第四权值调整模块；90.第二SVPWM逆变器；91.第四坐标变换模块；92.位移计算模块。In the figure: 1. Displacement controller; 2. Speed controller; 3. Bearingless permanent magnet synchronous motor; 11. First PID controller; 12. Second PID controller; 13. Force-current conversion module; 14. Section Four PI controller; 15. Fifth PI controller; 16. Third coordinate transformation module; 17. Angle calculation module; 21. First PI controller; 22. Second PI controller; 23. Third PI controller 24. The first coordinate transformation module; 25. The second coordinate transformation module; 26. The first SVPWM inverter; 27. The encoder; 28. The speed calculation module; 5. The vibration force compensation module; 51. The first neural network band-pass filter; 52. third PID controller; 53. second neural network band-pass filter; 54. fourth PID controller; 55. first weight adjustment module; 56. second weight adjustment module; 6. Dead zone vibration compensation module; 61. The third neural network bandpass filter; 62. The sixth PI controller; 63. The fourth neural network bandpass filter; 64. The seventh PI controller; 65. The third Weight adjustment module; 66. Fourth weight adjustment module; 90. Second SVPWM inverter; 91. Fourth coordinate transformation module; 92. Displacement calculation module.

具体实施方式Detailed ways

本发明的具体思想以及实施步骤为：Concrete thought of the present invention and implementation steps are:

参见图1，本发明所述的无轴承永磁同步电机神经网络带通滤波器振动补偿控制器由位移控制器1和转速控制器2组成，位移控制器1和转速控制器2的输出端连接无轴承永磁同步电机3，对无轴承永磁同步电机3实现控制。Referring to Figure 1, the bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of the present invention is composed of a displacement controller 1 and a rotational speed controller 2, and the output ends of the displacement controller 1 and the rotational speed controller 2 are connected The bearingless permanent magnet synchronous motor 3 controls the bearingless permanent magnet synchronous motor 3 .

对于转速控制器2，如图2所示，其采用速度电流双闭环控制，其由第一PI控制器21、第二PI控制器22、第三PI控制器23、第一坐标变换模块24、第二坐标变换模块25、第一SVPWM逆变器26、编码器27和速度计算模块28组成。其中，编码器27的输出端连接速度计算模块28，编码器27从无轴承永磁同步电机3的转轴处采集到转速脉冲信号并进行累加运算，将累加后的结果ΔP输入速度计算模块28，经速度计算模块28计算得到电机转子实际转速n，转速n计算公式为：For the speed controller 2, as shown in FIG. 2, it adopts the speed and current double closed-loop control, which consists of the first PI controller 21, the second PI controller 22, the third PI controller 23, the first coordinate transformation module 24, The second coordinate transformation module 25 , the first SVPWM inverter 26 , the encoder 27 and the speed calculation module 28 are composed. Wherein, the output end of the encoder 27 is connected to the speed calculation module 28, the encoder 27 collects the rotational speed pulse signal from the rotating shaft of the bearingless permanent magnet synchronous motor 3 and performs an accumulation operation, and the accumulated result ΔP is input to the speed calculation module 28, The actual speed n of the motor rotor is calculated by the speed calculation module 28, and the calculation formula of the speed n is:

Figure BDA0002946540100000041
Figure BDA0002946540100000041

式中：Ts为转速控制器2的中断周期；Le为编码器的线数。In the formula: T s is the interruption period of the speed controller 2; L e is the line number of the encoder.

将计算后的实际转速n与转速给定值n*作差，得到转速误差，并将该误差输入至第一PI控制器21，由第一PI控制器21调节后得到转矩绕组交轴电流给定值

Figure BDA0002946540100000042
与此同时，使用电流传感器采集无轴承永磁同步电机3的转矩两相绕组的转矩电流i2A和i2C，将转矩电流i2A和i2C输入到第二坐标变换模块25中，第二坐标变换模块25由Clarke变换和Park变换组成，经过第二坐标变换模块25对i2A和i2C转换后得到旋转坐标系下的转矩绕组交轴电流实际值iMq和转矩绕组直轴电流实际值iMd。以转矩绕组交轴电流给定值
Figure BDA0002946540100000043
和转矩绕组交轴电流实际值iMq的误差作为第二PI控制器22的输入，得到转矩绕组交轴电压给定值
Figure BDA0002946540100000044
以转矩绕组直轴电流
Figure BDA0002946540100000045
作为给定值，将
Figure BDA0002946540100000046
和转矩绕组直轴电流实际值iMd的误差作为第三PI控制器23的输入，得到转矩绕组直轴电压给定值
Figure BDA0002946540100000047
第二PI控制器22和第三PI控制器23的输出端均连接第一坐标变换模块24的输入端，第一坐标变换模块24由Park逆变换组成，该变换可将转矩绕组交轴电压给定值
Figure BDA0002946540100000048
和转矩绕组直轴电压给定值
Figure BDA0002946540100000049
转化为静止坐标系下的转矩绕组电压uMα和uMβ。第一坐标变换模块24的输出端依次串接第一SVPWM逆变器26和无轴承永磁同步电机3，第一坐标变换模块24将电压uMα和uMβ作为第一SVPWM逆变器26的输入，第一SVPWM逆变器26输出连接无轴承永磁同步电机3的输入，经第一SVPWM逆变器26得到无轴承永磁同步电机3的三相输入电压u2A、u2B、u2C。The difference between the calculated actual speed n and the given speed n * is obtained to obtain the speed error, and the error is input to the first PI controller 21, and the torque winding quadrature current is obtained after being adjusted by the first PI controller 21 Desired point
Figure BDA0002946540100000042
At the same time, use the current sensor to collect the torque currents i 2A and i 2C of the torque two-phase windings of the bearingless permanent magnet synchronous motor 3, and input the torque currents i 2A and i 2C into the second coordinate transformation module 25, The second coordinate transformation module 25 is composed of Clarke transformation and Park transformation, and after the second coordinate transformation module 25 converts i 2A and i 2C to obtain the torque winding quadrature current actual value i Mq and the torque winding direct current value under the rotating coordinate system Actual shaft current value i Md . The given value of the quadrature current of the torque winding
Figure BDA0002946540100000043
The error of the torque winding quadrature axis current actual value i Mq is used as the input of the second PI controller 22 to obtain the torque winding quadrature axis voltage given value
Figure BDA0002946540100000044
Direct axis current with torque winding
Figure BDA0002946540100000045
As a given value, the
Figure BDA0002946540100000046
The error of the torque winding direct axis current actual value i Md is used as the input of the third PI controller 23 to obtain the torque winding direct axis voltage given value
Figure BDA0002946540100000047
The output terminals of the second PI controller 22 and the third PI controller 23 are both connected to the input terminals of the first coordinate transformation module 24. The first coordinate transformation module 24 is composed of Park inverse transformation, which can convert the torque winding quadrature voltage Desired point
Figure BDA0002946540100000048
and torque winding direct axis voltage reference
Figure BDA0002946540100000049
Converted to torque winding voltages u Mα and u Mβ in the stationary coordinate system. The output end of the first coordinate transformation module 24 is serially connected to the first SVPWM inverter 26 and the bearingless permanent magnet synchronous motor 3 in sequence . Input, the output of the first SVPWM inverter 26 is connected to the input of the bearingless permanent magnet synchronous motor 3, and the three-phase input voltages u 2A , u 2B and u 2C of the bearingless permanent magnet synchronous motor 3 are obtained through the first SVPWM inverter 26 .

对于位移控制器1，如图3所示，其采用位移电流双闭环控制，其由第一PID控制器11、第二PID控制器12、振动力补偿模块5、力电流转换模块13、第四PI控制器14、第五PI控制器15、死区振动补偿模块6、第三坐标变换模块16、角度计算模块17、第二SVPWM逆变器90、第四坐标变换模块91、位移计算模块92和编码器27组成。其中，通过位移传感器采集无轴承永磁同步电机3的转子位置并输入位移计算模块92，位移计算模块92将采集到的位移信号转换为实际的x和y方向的位移，将x方向的实际位移x与给定值x*作差，得到位移误差，并将该误差输入至第一PID控制器11中，由第一PID控制器11调节后得到悬浮绕组x方向的力的给定值Fx；将y方向的实际位移y与给定值y*作差，得到位移误差，并将该误差输入至第二PID控制器82中，由第二PID控制器12调节后得到悬浮绕组y方向的力的给定值Fy。For the displacement controller 1, as shown in FIG. 3, it adopts the displacement current double closed-loop control, which consists of the first PID controller 11, the second PID controller 12, the vibration force compensation module 5, the force-current conversion module 13, the fourth PI controller 14 , fifth PI controller 15 , dead zone vibration compensation module 6 , third coordinate transformation module 16 , angle calculation module 17 , second SVPWM inverter 90 , fourth coordinate transformation module 91 , displacement calculation module 92 and encoder 27. Among them, the rotor position of the bearingless permanent magnet synchronous motor 3 is collected by the displacement sensor and input to the displacement calculation module 92, and the displacement calculation module 92 converts the collected displacement signal into the actual displacement in the x and y directions, and converts the actual displacement in the x direction. The difference between x and the given value x * is obtained to obtain the displacement error, and the error is input into the first PID controller 11 , and the given value F x of the force in the direction of the suspension winding x is obtained after adjustment by the first PID controller 11 ; The actual displacement y in the y direction is different from the given value y * to obtain the displacement error, and the error is input into the second PID controller 82, and the suspension winding y direction is obtained after being adjusted by the second PID controller 12. Force given value F y .

编码器27的输出端还连接角度计算模块17，编码器27输出的脉冲信号经过角度计算模块17得到转子机械角度θm，k时刻的转子机械角度计算过程为：The output end of the encoder 27 is also connected to the angle calculation module 17, and the pulse signal output by the encoder 27 obtains the rotor mechanical angle θ m through the angle calculation module 17. The rotor mechanical angle calculation process at time k is as follows:

Figure BDA0002946540100000051
Figure BDA0002946540100000051

式中：ΔP为编码器27输出的脉冲的累加结果。In the formula: ΔP is the cumulative result of the pulses output by the encoder 27 .

角度计算模块17和位移计算模块92的输出端均连接振动力补偿控制模块5的输入端，振动力补偿控制模块5以角度计算模块17输出的转子机械角度θm和位移计算模块92输出的转子实际位移x，y作为输入，获得补偿力Fxh和Fyh。The output ends of the angle calculation module 17 and the displacement calculation module 92 are all connected to the input end of the vibration force compensation control module 5, and the vibration force compensation control module 5 uses the rotor mechanical angle θ m output by the angle calculation module 17 and the rotor output by the displacement calculation module 92. The actual displacements x, y are taken as input, and the compensation forces F xh and F yh are obtained.

如图4所示，振动力补偿控制模块5由第一神经网络带通滤波器51、第二神经网络带通滤波器53和第三PID控制器52、第四PID控制器54组成。以x方向上的位移与转子机械角度θm作为第一神经网络带通滤波器51的输入，其输出的是振动位移

Figure BDA0002946540100000052
信号。x方向的第一神经网络带通滤波器51的具体结构如图6所示，其包括第一权值调整模块5，将实际位移x与第一神经网络带通滤波器51输出的振动位移
Figure BDA0002946540100000053
作差，得到误差信号ex，将误差信号ex与转子机械角度θm的正弦和余弦值作为第一权值调整模块55的输入，从而获得更新后的x方向上的权值ωx_1和ωx_2。第一神经网络带通滤波器51输出的振动位移
Figure BDA0002946540100000056
在k时刻的计算公式为：As shown in FIG. 4 , the vibration force compensation control module 5 is composed of a first neural network bandpass filter 51 , a second neural network bandpass filter 53 , a third PID controller 52 , and a fourth PID controller 54 . Taking the displacement in the x direction and the rotor mechanical angle θ m as the input of the first neural network band-pass filter 51, the output is the vibration displacement
Figure BDA0002946540100000052
Signal. The specific structure of the first neural network band-pass filter 51 in the x direction is shown in FIG. 6 , which includes a first weight adjustment module 5 , which compares the actual displacement x with the vibration displacement output by the first neural network band-pass filter 51 .
Figure BDA0002946540100000053
Make a difference to obtain the error signal e x , and use the sine and cosine values of the error signal e x and the rotor mechanical angle θ m as the input of the first weight adjustment module 55, so as to obtain the updated weight values in the x direction ω x_1 and ω x_2 . The vibration displacement output by the first neural network bandpass filter 51
Figure BDA0002946540100000056
The calculation formula at time k is:

Figure BDA0002946540100000054
Figure BDA0002946540100000054

权值ωx_1和ωx_2的计算过程采用如下公式：The calculation process of the weights ω x_1 and ω x_2 adopts the following formulas:

Figure BDA0002946540100000055
Figure BDA0002946540100000055

式中：ex为x方向上滤除谐波后的分量；ωx_1，ωx_2为x方向上更新的权值；μ1为步长因子。In the formula: e x is the component after harmonic filtering in the x direction; ω x_1 , ω x_2 are the updated weights in the x direction; μ 1 is the step factor.

从而得到x方向的振动位移

Figure BDA0002946540100000061
如图4，以0作为给定值与振动位移
Figure BDA0002946540100000062
作差，并将位移差值的结果作为第三PID控制器52的输入，经第三PID控制器52调节后获得振动补偿力Fxh。Thus, the vibration displacement in the x-direction is obtained
Figure BDA0002946540100000061
As shown in Figure 4, take 0 as the given value and the vibration displacement
Figure BDA0002946540100000062
Make a difference, and use the result of the displacement difference as the input of the third PID controller 52 , and obtain the vibration compensation force F xh after being adjusted by the third PID controller 52 .

第二神经网络带通滤波器53与第一神经网络带通滤波器51的结构和原理雷同。同理，以y方向上的位移与转子机械角度θm作为第二神经网络带通滤波器53的输入，y方向的第二神经网络带通滤波器53的具体结构如图7所示，将实际位移y与第二神经网络带通滤波器53输出的振动位移

Figure BDA0002946540100000063
作差，得到误差信号ey，并将误差信号ey与转子机械角度θm的正弦和余弦值作为第二权值调整模块56的输入，从而获得更新后的y方向上的权值ωy_1和ωy_2。第二神经网络带通滤波器53输出的k时刻的振动位移信号
Figure BDA0002946540100000064
的计算公式为：The second neural network bandpass filter 53 has the same structure and principle as the first neural network bandpass filter 51 . In the same way, the displacement in the y direction and the rotor mechanical angle θ m are used as the input of the second neural network bandpass filter 53. The specific structure of the second neural network bandpass filter 53 in the y direction is shown in FIG. 7. The actual displacement y and the vibration displacement output by the second neural network bandpass filter 53
Figure BDA0002946540100000063
Make a difference to obtain the error signal e y , and use the sine and cosine values of the error signal e y and the rotor mechanical angle θ m as the input of the second weight adjustment module 56, so as to obtain the updated weight value ω y_1 in the y direction and ω y_2 . The vibration displacement signal at time k output by the second neural network bandpass filter 53
Figure BDA0002946540100000064
The calculation formula is:

Figure BDA0002946540100000065
Figure BDA0002946540100000065

权值ωy_1和ωy_2的计算过程采用如下公式：The calculation process of the weights ω y_1 and ω y_2 adopts the following formulas:

Figure BDA0002946540100000066
Figure BDA0002946540100000066

式中：ey为y方向上滤除谐波后的分量；ωy_1，ωy_2为y方向上更新的权值；μ1为步长因子。In the formula: e y is the component after harmonic filtering in the y direction; ω y_1 , ω y_2 are the updated weights in the y direction; μ 1 is the step factor.

从而得到y方向的振动位移信号

Figure BDA0002946540100000067
如图4，以0作为给定值与振动位移信号
Figure BDA0002946540100000068
作差，并将位移差值的结果作为第四PID控制器54的输入，经第四PID控制器54调节后得到振动补偿力Fyh。Thereby, the vibration displacement signal in the y direction is obtained.
Figure BDA0002946540100000067
As shown in Figure 4, take 0 as the given value and the vibration displacement signal
Figure BDA0002946540100000068
Make a difference, and use the result of the displacement difference as the input of the fourth PID controller 54 , and obtain the vibration compensation force F yh after being adjusted by the fourth PID controller 54 .

将第一PID控制器11输出的x方向上的力Fx与振动力补偿模块5输出的x方向上的振动补偿力Fxh求和，与第二PID控制器12输出的y方向上的力Fy与振动力补偿模块5输出的y方向上的振动补偿力Fyh求和后一并输入给力电流转换模块13中，进而获得悬浮绕组的交直轴电流给定值

Figure BDA0002946540100000069
和
Figure BDA00029465401000000610
Summing the force F x in the x direction output by the first PID controller 11 and the vibration compensation force F xh in the x direction output by the vibration force compensation module 5, and the force in the y direction output by the second PID controller 12 F y and the vibration compensating force F yh in the y direction output by the vibration force compensating module 5 are summed and then input into the force-current conversion module 13, and then the AC-direction axis current given value of the suspension winding is obtained.
Figure BDA0002946540100000069
and
Figure BDA00029465401000000610

将得到的交直轴电流给定值

Figure BDA00029465401000000611
和
Figure BDA00029465401000000612
与悬浮绕组交直轴电流的实际电流iBq和iBd分别作差。其中，iBq和iBd通过电流传感器对无轴承永磁同步电机3的两相悬浮绕组电流进行采集，并将采集到的电流i1A和i1C输入至第四坐标变换模块91中，第四坐标变换模块91由Clarke变换和Park变换组成，i1A和i1C经过第四坐标变换模块91即可获得悬浮绕组交直轴的实际电流iBq和iBd，将
Figure BDA00029465401000000613
与iBq作差后的结果输入至第四PI控制器14中，进而获得悬浮绕组交轴控制电压uBq；将
Figure BDA00029465401000000614
与iBd作差后的结果输入至第五PI控制器15中，进而获得悬浮绕组直轴控制电压uBd。The given value of AC and direct axis current will be obtained
Figure BDA00029465401000000611
and
Figure BDA00029465401000000612
Differences with the actual currents i Bq and i Bd of the AC and DC axis currents of the suspension windings respectively. Among them, i Bq and i Bd collect the two-phase suspension winding current of the bearingless permanent magnet synchronous motor 3 through the current sensor, and input the collected currents i 1A and i 1C into the fourth coordinate transformation module 91, the fourth The coordinate transformation module 91 is composed of Clarke transformation and Park transformation, i 1A and i 1C can obtain the actual currents i Bq and i Bd of the quadrature axis of the suspension winding through the fourth coordinate transformation module 91 .
Figure BDA00029465401000000613
The result after the difference with i Bq is input into the fourth PI controller 14, and then obtains the suspension winding quadrature axis control voltage u Bq ;
Figure BDA00029465401000000614
The result of the difference with i Bd is input to the fifth PI controller 15 to obtain the suspension winding direct axis control voltage u Bd .

以转子电角度θe和悬浮绕组交轴电流实际值iBq、悬浮绕组直轴电流实际值iBd一并输入至死区振动补偿模块6中得到补偿电压uBqh和uBdh。其中，通过编码器27采集的无轴承永磁同步电机3的脉冲信号经角度计算模块17后得到转子电角度θe，计算过程为：The rotor electrical angle θ e , the actual value of the suspension winding quadrature axis current i Bq , and the actual value of the suspension winding direct axis current i Bd are input to the dead zone vibration compensation module 6 to obtain the compensation voltages u Bqh and u Bdh . Wherein, the pulse signal of the bearingless permanent magnet synchronous motor 3 collected by the encoder 27 is passed through the angle calculation module 17 to obtain the rotor electrical angle θ e , and the calculation process is as follows:

θe(k)＝PMθm(k) (7)θ e (k) = P M θ m (k) (7)

式中：θm(k)为公式(2)中k时刻的转子机械角度；PM为转矩绕组极对数。In the formula: θ m (k) is the mechanical angle of the rotor at time k in formula (2); P M is the number of pole pairs of the torque winding.

将得到的转子电角度θe与交直轴电流实际值iBq和iBd一并输入至死区振动补偿模块6，死区振动补偿模块6由直轴方向第三神经网络带通滤波器61、交轴第四神经网络带通滤波器63以及第六PI控制器62、第七PI控制器64组成。在死区振动补偿模块6中，直轴方向与交轴方向的补偿如图5所示。以直轴方向上的电流iBd与转子电角度θe的6倍作为直轴方向的第三神经网络带通滤波器61的输入，从而得到直轴方向的谐波电流信号

Figure BDA0002946540100000071
其中，直轴方向第三神经网络带通滤波器61的内部结构原理图如图8所示，其包括第三权值调整模块65。图8中，将直轴方向上的电流iBd与第三神经网络带通滤波器61输出的谐波电流信号
Figure BDA0002946540100000072
作差，获得误差信号eBd，将误差信号eBd与转子电角度θe的6倍的正余弦值作为第三权值调整模块65的输入，从而获得更新后的直轴方向上的权值ωd6_1和ωd6_2。第三神经网络带通滤波器61输出的k时刻的谐波电流
Figure BDA0002946540100000073
的计算公式为：The obtained rotor electrical angle θ e is input to the dead zone vibration compensation module 6 together with the actual values of the AC and direct axis currents i Bq and i Bd . The dead zone vibration compensation module 6 is composed of the third neural network bandpass filter 61 in the direct axis direction, The quadrature-axis fourth neural network bandpass filter 63 , the sixth PI controller 62 and the seventh PI controller 64 are composed. In the dead zone vibration compensation module 6, the compensation in the direction of the direct axis and the direction of the quadrature axis is shown in FIG. 5 . Taking the current i Bd in the direct axis direction and 6 times the rotor electrical angle θ e as the input of the third neural network bandpass filter 61 in the direct axis direction, the harmonic current signal in the direct axis direction is obtained.
Figure BDA0002946540100000071
The schematic diagram of the internal structure of the third neural network bandpass filter 61 in the direct axis direction is shown in FIG. 8 , which includes a third weight adjustment module 65 . In FIG. 8 , the current i Bd in the direct axis direction is compared with the harmonic current signal output by the third neural network bandpass filter 61
Figure BDA0002946540100000072
Make a difference to obtain the error signal e Bd , and use the error signal e Bd and the sine and cosine value of the rotor electrical angle θ e 6 times as the input of the third weight adjustment module 65, so as to obtain the updated weight in the direct axis direction ω d6_1 and ω d6_2 . The harmonic current at time k output by the third neural network bandpass filter 61
Figure BDA0002946540100000073
The calculation formula is:

Figure BDA0002946540100000074
Figure BDA0002946540100000074

权值ωd6_1和ωd6_2的计算过程采用如下公式：The calculation process of the weights ω d6_1 and ω d6_2 adopts the following formulas:

Figure BDA0002946540100000075
Figure BDA0002946540100000075

式中：eBd为直轴方向上滤除谐波后的分量；ωd6_1，ωd6_2为直轴方向上更新的6次谐波的权值；μ2为步长因子。In the formula: e Bd is the component after harmonic filtering in the direction of the direct axis; ω d6_1 , ω d6_2 are the updated weights of the 6th harmonic in the direction of the direct axis; μ 2 is the step factor.

从而得到直轴方向的谐波电流信号

Figure BDA0002946540100000076
如图5中，以0作为给定值与谐波电流信号
Figure BDA0002946540100000077
作差，并将结果作为第六PI控制器62的输入，经第六PI控制器62调节后得到直轴补偿电压uBdh。Thereby, the harmonic current signal in the direct axis direction is obtained.
Figure BDA0002946540100000076
As shown in Figure 5, take 0 as the given value and the harmonic current signal
Figure BDA0002946540100000077
Make a difference, and use the result as the input of the sixth PI controller 62 , and obtain the direct-axis compensation voltage u Bdh after being adjusted by the sixth PI controller 62 .

交轴第四神经网络带通滤波器63和第三神经网络带通滤波器61的结构雷同。同理，以交轴方向上的电流iBq与转子电角度θe的6倍作为交轴第四神经网络带通滤波器63的输入，从而得到直轴方向的谐波电流信号

Figure BDA0002946540100000078
其中，交轴方向第四神经网络带通滤波器63的内部结构原理图如图9所示，其包括第四权值调整模块66。图9中，将交轴方向上的电流iBq与第四神经网络带通滤波器63输出的谐波电流信号
Figure BDA0002946540100000081
作差，获得电流误差eBq信号，将电流误差eBq信号与转子电角度θe的6倍的正余弦值作为第四权值调整模块66的输入，从而获得更新后的直轴方向上的权值ωq6_1和ωq6_2。第四神经网络带通滤波器63输出谐波电流
Figure BDA0002946540100000082
k时刻的谐波电流
Figure BDA0002946540100000083
的计算公式为：The structures of the fourth neural network bandpass filter 63 and the third neural network bandpass filter 61 are the same. In the same way, the current i Bq in the quadrature axis direction and 6 times the rotor electrical angle θ e are used as the input of the quadrature axis fourth neural network bandpass filter 63, so as to obtain the harmonic current signal in the quadrature axis direction.
Figure BDA0002946540100000078
The schematic diagram of the internal structure of the fourth neural network bandpass filter 63 in the quadrature axis direction is shown in FIG. 9 , which includes a fourth weight adjustment module 66 . In FIG. 9 , the current i Bq in the quadrature axis direction is compared with the harmonic current signal output by the fourth neural network bandpass filter 63
Figure BDA0002946540100000081
Make a difference, obtain the current error e Bq signal, and use the current error e Bq signal and the sine and cosine value of the rotor electrical angle θ e 6 times as the input of the fourth weight adjustment module 66, so as to obtain the updated straight axis direction. The weights ω q6_1 and ω q6_2 . The fourth neural network band-pass filter 63 outputs the harmonic current
Figure BDA0002946540100000082
Harmonic current at time k
Figure BDA0002946540100000083
The calculation formula is:

Figure BDA0002946540100000084
Figure BDA0002946540100000084

权值ωd6_1和ωd6_2的计算过程采用如下公式：The calculation process of the weights ω d6_1 and ω d6_2 adopts the following formulas:

Figure BDA0002946540100000085
Figure BDA0002946540100000085

式中：eBq为交轴方向上滤除谐波后的分量；ωq6_1和ωq6_2为交轴方向上更新的6次谐波的权值；μ2为步长因子。In the formula: e Bq is the component after harmonic filtering in the quadrature axis direction; ω q6_1 and ω q6_2 are the updated weights of the 6th harmonic in the quadrature axis direction; μ 2 is the step factor.

从而得到直轴方向的谐波电流信号

Figure BDA0002946540100000086
如图5所示，以0作为给定值与谐波电流信号
Figure BDA0002946540100000087
作差，并将结果作为第七PI控制器64的输入，经第七PI控制器64调节后得到交轴补偿电压uBqh。Thereby, the harmonic current signal in the direct axis direction is obtained.
Figure BDA0002946540100000086
As shown in Figure 5, taking 0 as a given value and the harmonic current signal
Figure BDA0002946540100000087
Make a difference, and use the result as the input of the seventh PI controller 64 , and obtain the quadrature axis compensation voltage u Bqh after being adjusted by the seventh PI controller 64 .

将第四PI控制器14输出的直轴方向上的电压uBd与死区振动补偿模块中输出的直轴补偿电压uBdh相加，获得直轴指令电压

Figure BDA0002946540100000088
将第五PI控制器15输出的交轴方向上的电压uBq与死区振动补偿模块中输出的交轴补偿电压uBqh相加，获得交轴指令电压
Figure BDA0002946540100000089
将得到的
Figure BDA00029465401000000810
与
Figure BDA00029465401000000811
作为第三坐标变换模块16的输入，第三坐标变换模块16由Park反变换组成，经第三坐标变换模块16后得到静止坐标系下的悬浮绕组电压uBα和uBβ。The voltage u Bd in the direct axis direction output by the fourth PI controller 14 is added with the direct axis compensation voltage u Bdh output in the dead zone vibration compensation module to obtain the direct axis command voltage
Figure BDA0002946540100000088
Add the voltage u Bq in the quadrature axis direction output by the fifth PI controller 15 and the quadrature axis compensation voltage u Bqh output in the dead zone vibration compensation module to obtain the quadrature axis command voltage
Figure BDA0002946540100000089
will get
Figure BDA00029465401000000810
and
Figure BDA00029465401000000811
As the input of the third coordinate transformation module 16, the third coordinate transformation module 16 is composed of inverse Park transformation, and after the third coordinate transformation module 16, the suspension winding voltages u Bα and u Bβ in the static coordinate system are obtained.

将悬浮绕组电压uBα和uBβ作为第二SVPWM逆变器90的输入，第二SVPWM逆变器90输出连接无轴承永磁同步电机3的输入，经第二SVPWM逆变器90得到无轴承永磁同步电机3的三相输入电压u1A、u1B、u1C。The suspension winding voltages u Bα and u Bβ are used as the input of the second SVPWM inverter 90, the output of the second SVPWM inverter 90 is connected to the input of the bearingless permanent magnet synchronous motor 3, and the bearingless motor is obtained through the second SVPWM inverter 90. The three-phase input voltages u 1A , u 1B and u 1C of the permanent magnet synchronous motor 3 .

图10示出的是本发明电机振动补偿控制器结构的总体实现原理框图，通过位移控制器1、转速控制器2以及对其中各个模块进行设计，对速度闭环和位置闭环调节器参数进行调整，实现速度闭环控制和振动补偿控制。其中，转速控制器2采用常用的直轴指令电流为0的矢量控制方法进行调速控制，位移控制器1中通过对位移的调节完成矢量控制，使无轴承永磁同步电机3的转子保持稳定运行，并通过振动力补偿模块5对位移信号中的偏心振动信号进行补偿控制，同时利用死区振动补偿控制模块6对由死区效应引起的存在于电流中的高次谐波信号进行再次补偿，可实现更加精确的振动补偿控制。Figure 10 shows the overall realization principle block diagram of the motor vibration compensation controller structure of the present invention, through the displacement controller 1, the rotational speed controller 2 and the design of each module, the speed closed-loop and position closed-loop regulator parameters are adjusted, Realize speed closed-loop control and vibration compensation control. Among them, the speed controller 2 adopts the commonly used vector control method with the direct-axis command current of 0 for speed regulation control, and the displacement controller 1 completes the vector control by adjusting the displacement, so that the rotor of the bearingless permanent magnet synchronous motor 3 remains stable run, and compensate and control the eccentric vibration signal in the displacement signal through the vibration force compensation module 5, and use the dead zone vibration compensation control module 6 to re-compensate the high-order harmonic signal existing in the current caused by the dead zone effect. , which can realize more precise vibration compensation control.

根据以上所述，便可实现本发明。对本领域的技术人员在不背离本发明的精神和保护范围的情况下做出的其它的变化和修改，仍包括在本发明保护范围之内。From the above, the present invention can be realized. Other changes and modifications made by those skilled in the art without departing from the spirit and protection scope of the present invention are still included in the protection scope of the present invention.

Claims (10)

1. The utility model provides a no bearing PMSM neural network band-pass filter vibration compensation controller which comprises displacement controller (1) and rotational speed controller (2), characterized by: the displacement controller (1) comprises a vibration force compensation control module (5) and a dead zone vibration compensation module (6);
the vibration force compensation control module (5) performs actual displacement x, y in x and y directions and a rotor mechanical angle thetamAs input, a corresponding vibration compensation force F is outputxh，FyhThe neural network band-pass filter comprises a first neural network band-pass filter (51), a second neural network band-pass filter (53), a third PID controller (52) and a fourth PID controller (54); the first neural network band-pass filter (51) is used for measuring the actual displacement x and the mechanical angle theta of the rotor in the x directionmAs input, output vibrational displacement
Figure FDA0003491688510000011
Given value of 0 and vibration displacement
Figure FDA0003491688510000012
Taking the difference and using the difference as an input to a third PID controller (52), the third PID controller (52) outputting a vibration compensation force Fxh(ii) a The actual displacement y of the second neural network band-pass filter (53) in the y direction and the mechanical angle theta of the rotormAs input, output vibrational displacement
Figure FDA0003491688510000013
Given value of 0 and vibration displacement
Figure FDA0003491688510000014
Taking the difference as an input to a fourth PID controller (54), the fourth PID controller (54) outputting a vibration compensation force Fyh(ii) a Said vibration compensation force FxhGiven value F of force in x direction of levitation windingxAfter summing, the sum is input to a force current conversion module (13); said vibration compensation force FyhGiven value F of force in y direction of levitation windingyThe summed values are input to a force current conversion module (13), and the current conversion module (13) obtains the given value of the quadrature-direct axis current
Figure FDA0003491688510000015
And
Figure FDA0003491688510000016
the dead zone vibration compensation module (6) uses a rotor electrical angle thetaeAnd the actual current i of the quadrature-direct axis currentBq，iBdAs input, the AC-DC axis compensation voltage u is outputBqh，uBdhThe device comprises a third neural network band-pass filter (61) in the direction of a direct axis, a fourth neural network band-pass filter (63) in the direction of a quadrature axis, a sixth PI controller (62) and a seventh PI controller (64), wherein the third neural network band-pass filter (61) uses actual current i in the direction of the direct axisBdAnd 6 times the rotor electrical angle thetaeAs input, obtaining harmonic current in the direction of the direct axis
Figure FDA0003491688510000017
With 0 as given value and harmonic current
Figure FDA0003491688510000018
Taking the difference and the result as the input of the sixth PI controller (62), the sixth PI controller (62) obtains the direct axis compensation voltageuBdhThe control voltage u in the direction of the straight axisBdWith compensation voltage u of the direct axisBdhAdding to obtain direct axis command voltage
Figure FDA0003491688510000019
The fourth neural network band-pass filter (63) uses the actual current i in the quadrature axis directionBqAnd 6 times the rotor electrical angle thetaeAs input, harmonic current in quadrature direction is obtained
Figure FDA00034916885100000110
With 0 as given value and harmonic current
Figure FDA00034916885100000111
Taking the difference and the result as the input of a seventh PI controller (64), the seventh PI controller (64) obtains the quadrature axis compensation voltage uBqhWill control the voltage u in the quadrature axis directionBqAnd quadrature axis compensation voltage uBqhAdding to obtain quadrature axis command voltage
Figure FDA00034916885100000112
2. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 1, characterized in that: the first neural network band-pass filter (51) in the x direction comprises a first weight value adjusting module (55), and the actual displacement x and the vibration displacement
Figure FDA00034916885100000113
Difference is made to obtain error exError exMechanical angle theta to rotormThe sine and cosine values are used as the input of a first weight value adjusting module (55) to obtain the updated weight value omega in the x directionx_1And ωx_2(ii) a The second neural network band-pass filter (53) comprises a second weight adjusting module (56) which adjusts the actual displacement y and the vibration displacement
Figure FDA0003491688510000021
Differencing to obtain an error signal eyWill error signal eyMechanical angle theta to rotormThe sine and cosine values are used as the input of a second weight value adjusting module (56) to obtain the updated weight value omega in the y directiony_1And ωy_2。
3. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 2, characterized in that: vibration displacement at time k
Figure FDA0003491688510000022
Wherein, ω isx_1(k+1)＝ωx_1(k)+2μ1excosθm，ωx_2(k+1)＝ωx_2(k)+2μ1exsinθm，ωx_1，ωx_2The weight value updated in the x direction; mu.s1Is the step size factor.
4. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 1, characterized in that: the third neural network band-pass filter (61) comprises a third weight adjusting module (65) and a current i in the direction of the straight axisBdAnd the harmonic current signal output by the third neural network band-pass filter (61)
Figure FDA0003491688510000023
Differencing to obtain a current error eBdError of current eBdAnd sin6 thetae、cos6θeAs an input of a third weight adjustment module (65), obtaining an updated weight ω in the direction of the straight axisd6_1And ωd6_2The third neural network band-pass filter (61) outputs harmonic current
Figure FDA0003491688510000024
The fourth neural network band-pass filter (63) comprises a fourth weight value adjusting module (66) and a current i in the quadrature axis directionBqAnd the harmonic current signal output by the fourth neural network band-pass filter (63)
Figure FDA0003491688510000025
Differencing to obtain a current error eBqSignal, current error eBqAnd sin6 thetae、cos6θeAs the input of a fourth weight value adjusting module (66), the updated weight value omega in the direction of the straight axis is obtainedq6_1And ωq6_2Output harmonic current
Figure FDA0003491688510000026
5. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 4, which is characterized in that: harmonic current at time k
Figure FDA0003491688510000027
Wherein, ω isd6_1(k+1)＝ωd6_1(k)+2μ2eBdcos6θe，ωd6_2(k+1)＝ωd6_2(k)+2μ2eBdsin6θe，ωd6_1，ωd6_2For the weight of the 6 th harmonic updated in the direction of the direct axis, mu2Is the step size factor.
6. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 1, characterized in that: actual displacement x and given value x in x direction*Obtaining a displacement error by difference making, inputting the error into a first PID controller (11), and obtaining a given value F of the force in the x direction of the suspension winding after being adjusted by the first PID controller (11)x(ii) a The actual displacement y in the y direction is compared with a given value y*The difference is made to obtain a displacement error, the displacement error is input into a second PID controller (12), and the given value F of the force in the y direction of the suspension winding is obtained after the adjustment of the second PID controller (12)y。
7. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 1, characterized in that: collecting two-phase suspension winding current of a bearingless permanent magnet synchronous motor and collecting current i1AAnd i1CInput to a fourth coordinate transformation module (91), and the actual current i of the AC-DC axis of the suspension winding is obtained through the fourth coordinate transformation module (91)BqAnd iBd(ii) a The given value of the quadrature-direct axis current
Figure FDA0003491688510000031
And
Figure FDA0003491688510000032
and the actual current iBqAnd iBdThe difference is respectively made and the result is inputted into the corresponding fourth PI controller (14) and the fifth PI controller (15), the fourth PI controller (14) outputs the control voltage u in the direction of the straight shaftBdA fifth PI controller (15) outputs the control voltage u in the quadrature axis directionBq。
8. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 1, characterized in that: the said direct and alternating axis command voltage
Figure FDA0003491688510000033
And
Figure FDA0003491688510000034
the third coordinate transformation module (16) is used as the input of the third coordinate transformation module (16), and the third coordinate transformation module (16) outputs the suspension winding voltage u under the static coordinate systemBαAnd uBβVoltage u of the levitation windingBαAnd uBβThe second SVPWM inverter (90) obtains a three-phase input voltage u of the bearingless permanent magnet synchronous motor as an input of the second SVPWM inverter (90)1A、u1B、u1C。
9. According to the claimsSolving 1 the vibration compensation controller of the bearingless permanent magnet synchronous motor neural network band-pass filter is characterized in that: an encoder is adopted to collect pulse signals of the bearingless permanent magnet synchronous motor, and the mechanical angle of the rotor at the moment k is obtained through an angle calculation module (17)
Figure FDA0003491688510000035
Delta P is the accumulated result of the pulses output by the encoder, LeIs the number of lines of the encoder.
10. The bearingless permanent magnet synchronous motor neural network band-pass filter vibration compensation controller of claim 9, wherein: rotor electrical angle theta at time ke(k)＝PMθm(k)，θm(k) Mechanical angle of rotor at time k, PMIs the torque winding pole pair number.
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A Vibration Reduction Method of One-Axis Actively Position Regulated Single-Drive Bearingless Motor With Repulsive Passive Magnetic Bearings;Hiroya Sugimoto etal.;《IEEE Transactions on Industry Applications》;20160229;第52卷(第1期);全文 *
无轴承异步电机动不平衡振动补偿控制;詹立新 等;《电工技术学报》;20141130;第29卷(第11期);全文 *

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